BacteriaPI

The approximate kernel density estimates of the 813 bacterial 
organisms' isoelectric point (pI) protein distributions.

An implementation of the methodology described in
Petersen and Mueller (2016) <doi:10.1214/15-AOS1363> for the functional
data analysis of samples of density functions. Densities are first
transformed to their corresponding log quantile densities, followed by
ordinary Functional Principal Components Analysis (FPCA). Transformation
modes of variation yield improved interpretation of the variability in the
data as compared to FPCA on the densities themselves. The standard
fraction of variance explained (FVE) criterion commonly used for functional
data is adapted to the transformation setting, also allowing for an
alternative quantification of variability for density data through the
Wasserstein metric of optimal transport.

Alexander Petersen

fdadensity

Functional Data Analysis for Density Functions by Transformation
to a Hilbert Space

A. Petersen

H.G. Mueller

BacteriaPI function

A matrix with 813 rows and 768 columns:<dl>
<dt>rowname</dt>
<dd>General organism identifier</dd><dt>colspace</dt>
<dd>pH in [0,14]</dd>
</dl>

Format

pH distribution of 813 bacterial organisms — BacteriaPI

A matrix with 813 rows and 768 columns:<dl>
<dt>rowname</dt>
<dd>General organism identifier</dd>

<dt>colspace</dt>
<dd>pH in [0,14]</dd>


</dl>

BacteriaPI: pH distribution of 813 bacterial organisms

Description

Arguments

Format

References